Joint segmentation of wind speed and direction using a hierarchical model
From MaRDI portal
Publication:1020656
DOI10.1016/j.csda.2007.04.016zbMath1445.62303OpenAlexW2130066308WikidataQ58830408 ScholiaQ58830408MaRDI QIDQ1020656
Nicolas Dobigeon, Jean-Yves Tourneret
Publication date: 2 June 2009
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2007.04.016
Related Items
On a nonparametric change point detection model in Markovian regimes, Joint segmentation of multivariate Gaussian processes using mixed linear models, Efficient Bayesian analysis of multiple changepoint models with dependence across segments, Modified dynamic programming approach for offline segmentation of long hydrometeorological time series, Statistical modeling of directional data using a robust hierarchical von Mises distribution model: perspectives for wind energy
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Bayesian off-line detection of multiple change-points corrupted by multiplicative noise: Application to SAR image edge detection
- Joint segmentation of the wind speed and direction
- On the influence of the proposal distributions on a reversible jump MCMC algorithm applied to the detection of multiple change-points
- Inference from iterative simulation using multiple sequences
- Least‐squares Estimation of an Unknown Number of Shifts in a Time Series
- Bayesian inference for the von Mises-Fisher distribution
- Use of Cumulative Sums of Squares for Retrospective Detection of Changes of Variance
- Joint Segmentation of Multivariate Astronomical Time Series: Bayesian Sampling With a Hierarchical Model
- Joint Segmentation of Piecewise Constant Autoregressive Processes by Using a Hierarchical Model and a Bayesian Sampling Approach
- Coupling a stochastic approximation version of EM with an MCMC procedure
- Exact Bayesian curve fitting and signal segmentation
- Gaussian model selection
